practical-time-series-analysis.pdf
11.8 MB
Practical Time Series Analysis with Python #book
A spreadsheet on attractors, their properties and descriptions #chaostheory #attractors
https://www.epfl.ch/labs/dynnet/ Dynamical Neural Networks described by an attractors under the hood #dynamicneuralnetworks #stochasticprocess #deeplearning #oscillatoryneuralnetwork #chaostheory
9708_122.pdf
123.7 KB
Введение в негладкий анализ #негладкийанализ #матоптимизация
WaveletTutorial.pdf
1.7 MB
Simple introduction into Wavelet Transformations
SelectiveNet - a more robust and elastic approach to Deep Learning #deeplearning #selectivenet #neuralnetwork
Кстати, для тех кто хотят получить более широкое математическое образование без формального обучения.
Эту книжечку можно (и нужно) использовать как карту/гайд к современной математике. Написал один межнаровец в MIT и сейчас достаточно широкий коммюнити помогает поддерживать эту "карту".
(на 15й странице есть список разделов)
https://venhance.github.io/napkin/Napkin.pdf
Эту книжечку можно (и нужно) использовать как карту/гайд к современной математике. Написал один межнаровец в MIT и сейчас достаточно широкий коммюнити помогает поддерживать эту "карту".
(на 15й странице есть список разделов)
https://venhance.github.io/napkin/Napkin.pdf
Forwarded from Лекса Лакер
https://github.com/facebookresearch/pytorch3d
Там 3д пайторч выпустили
Там 3д пайторч выпустили
GitHub
GitHub - facebookresearch/pytorch3d: PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data - facebookresearch/pytorch3d
Forwarded from Halyna
Position: Junior Data Scientist
Company: 1touch.io
Location: Kyiv, Ukraine
Estimated salary: $1000-1500
We are looking for a junior data scientist who’s willing to participate in the development of an AI module, which is responsible for end-to-end processing of any kind of text data, which comes to the application. You will join a team of talented people who work collaboratively between developers, quality engineers, product managers, DevOps and usability experts to make our products leaders in the international market
Role description:
As part of your role you will help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products.
Responsibilities:
research of latest advances in the sphere of NLP to continuously deliver new approaches and support existing pipelines;
integration testing, unit testing and benchmarking the code;
assistance with the all of the steps of ML cycle: feature engineering, model development, model training, model evaluation and prediction, pipeline integration and deployment;
performing of all of the data preprocessing steps: data fetching, data preprocessing, data labeling and cleaning;
assistance with creation of Docker containers, Gitlab CI, etc.;
development and support of rule-based structured data processing system;
creation of basic documentation for the repo.
Requirement & skills:
proficiency with Python 3.x;
basic knowledge of tensorflow/pytorch, gensim, scikit-learn, keras, spacy, numpy, and similar ML libraries;
basic understanding of how message brokers, CI pipelines, shell scripting work;
basic understanding of statistics and probability theory;
basic understanding and experience of implementation of basic NLP approaches;
strong understanding of business requirements;
desire to participate in end-to-end delivery cycle, which includes both high-level and low-level tasks (e.g. regexes development and data labeling);
experience with deep learning
A sharp eye for detail, research skills and the ability to work under strict deadlines;
Ability to communicate with other team members in English;
Nice to have:
basic knowledge of Java;
experience with Docker containers and services;
advanced English knowledge;
Benefits
Comfortable offices in city center
Friendly and highly professional atmosphere, laptop or workstation, corporate events
Benefits package including competitive salary, medical insurance, bonuses and annual salary reviews
Paid 14 sick leaves,20 vacations and national holidays
Great opportunities for professional growth and advancement
Reimbursement for transportation expenses for out of town employees, parking place as an option
Comfortable office facilities (kitchens, coffee/tea points, etc.)
Company: 1touch.io
Location: Kyiv, Ukraine
Estimated salary: $1000-1500
We are looking for a junior data scientist who’s willing to participate in the development of an AI module, which is responsible for end-to-end processing of any kind of text data, which comes to the application. You will join a team of talented people who work collaboratively between developers, quality engineers, product managers, DevOps and usability experts to make our products leaders in the international market
Role description:
As part of your role you will help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products.
Responsibilities:
research of latest advances in the sphere of NLP to continuously deliver new approaches and support existing pipelines;
integration testing, unit testing and benchmarking the code;
assistance with the all of the steps of ML cycle: feature engineering, model development, model training, model evaluation and prediction, pipeline integration and deployment;
performing of all of the data preprocessing steps: data fetching, data preprocessing, data labeling and cleaning;
assistance with creation of Docker containers, Gitlab CI, etc.;
development and support of rule-based structured data processing system;
creation of basic documentation for the repo.
Requirement & skills:
proficiency with Python 3.x;
basic knowledge of tensorflow/pytorch, gensim, scikit-learn, keras, spacy, numpy, and similar ML libraries;
basic understanding of how message brokers, CI pipelines, shell scripting work;
basic understanding of statistics and probability theory;
basic understanding and experience of implementation of basic NLP approaches;
strong understanding of business requirements;
desire to participate in end-to-end delivery cycle, which includes both high-level and low-level tasks (e.g. regexes development and data labeling);
experience with deep learning
A sharp eye for detail, research skills and the ability to work under strict deadlines;
Ability to communicate with other team members in English;
Nice to have:
basic knowledge of Java;
experience with Docker containers and services;
advanced English knowledge;
Benefits
Comfortable offices in city center
Friendly and highly professional atmosphere, laptop or workstation, corporate events
Benefits package including competitive salary, medical insurance, bonuses and annual salary reviews
Paid 14 sick leaves,20 vacations and national holidays
Great opportunities for professional growth and advancement
Reimbursement for transportation expenses for out of town employees, parking place as an option
Comfortable office facilities (kitchens, coffee/tea points, etc.)
Quantum computing sandbox. Parallel your research on the quantum processing unit: https://quantum-computing.ibm.com/
IBM Quantum
Program real quantum systems with the leading quantum cloud application.
Forwarded from Halyna
YouTube
WiDS TLV 2020- Halyna Oliinyk- Tips for Hardware Acceleration of Tensorflow-based ML Service
Tips and Tricks for Hardware Acceleration of Tensorflow-based ML Service
The talk will be dedicated to the research of performance best practices for tensorflow-based AI system running either on GPU or CPU. It will cover a brief review of best and worst…
The talk will be dedicated to the research of performance best practices for tensorflow-based AI system running either on GPU or CPU. It will cover a brief review of best and worst…
https://ai.googleblog.com/2020/03/announcing-tensorflow-quantum-open.html - Quantum Machine Learning with TesnsorFlow? Sounds like Cyberpunk? Let's take a look
blog.research.google
Announcing TensorFlow Quantum: An Open Source Library for Quantum Machine Learning
2003.02989.pdf
2.5 MB
TensorFlow Quantum: a framework for Quantum Machine Learning (whitepaper)
https://youtu.be/-ZNEzzDcllU Google's Quantum Supremacy
YouTube
Demonstrating Quantum Supremacy
We’re marking a major milestone in quantum computing research that opens up new possibilities for this technology. Learn how the Google AI Quantum team demonstrated how a quantum computer can perform a task no classical computer can in an experiment called…
You don't know how to spend your quarantine time and you're a complete beginner? Here are top 5 free courses list:
1. mlcourse.ai
2. course18.fast.ai/ml
3. dlcourse.ai
4. kaggle.com/learn/overview
5. course.fast.ai
1. mlcourse.ai
2. course18.fast.ai/ml
3. dlcourse.ai
4. kaggle.com/learn/overview
5. course.fast.ai
Kaggle
Learn Python, Data Viz, Pandas & More | Tutorials | Kaggle
Practical data skills you can apply immediately: that's what you'll learn in these no-cost courses. They're the fastest (and most fun) way to become a data scientist or improve your current skills.